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Preprocessing the Reciprocity Gap Sampling Method in Buried-Object Imaging Experiments

delete2010-10-01
delete18
PRE
AI
Ö
Özgür Özdemir *
H
Houssem Haddar
DOI:10.1109/LGRS.2010.2047003delete
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Abstract

Abstract

En 中文
A reciprocity gap linear sampling method (RG-LSM) coupled with an analytic continuation method is proposed to localize and retrieve the shape of objects buried under a rough surface from multistatic data at a fixed frequency. The obtained procedure makes feasible the application of the RG-LSM algorithm to imaging experiments where the data are collected in the upper domain. It does not require the computation of the Green's function of the background layered medium and also does not require any a priori knowledge on the number or the physical properties of the buried scatterers. The efficiency and robustness of the method are validated through various numerical experiments for single and multiconnected objects.
Keywords:
Analytic continuation method
inverse scattering
reciprocity gap linear sampling method (RG-LSM)
rough surface

Journal

IEEE Geoscience and Remote Sensing Magazine cover
IEEE Geoscience and Remote Sensing Magazine
IF:
16.4
Papers:
1.0W
Citations:
5.1K

Organization

I
Istanbul Technical University
Scholars:
8.9K
Papers: 7.8K
Citations: 7.9K
I
institut polytechnique de paris
Scholars:
1.3W
Papers: 1.0W
Citations: 6